Long term <i>in vivo</i> degradation and tissue response to photo‐cross‐linked elastomers prepared from star‐shaped prepolymers of poly(ε‐caprolactone‐<i>co</i>‐<scp>D,L</scp>‐lactide)
Bibliographic record
Abstract
Long term in vivo degradation, and tissue response to, cylindrical elastomers made of photo-cross-linked star-poly(epsilon-caprolactone-co-D,L-lactide) triacrylate were investigated through subcutaneous implantation in rats. The elastomers were prepared via UV initiated crosslinking of prepolymers of equimolar amounts of monomers; a high crosslink density elastomer (ELAST 1250) was prepared from a prepolymer of 1250 Da and a low crosslink density elastomer (ELAST 7800) was prepared from a prepolymer of 7800 Da. The elastomers were characterized using cross-polarization magic angle spinning solid state (13)C NMR and attenuated total reflectance fourier transform infrared spectroscopy. The progress of the in vivo degradation process was followed by employing SEM, uniaxial tensile, mass loss, water uptake, and sol content measurements. The rate of in vivo degradation was faster than the rate of in vitro degradation for both ELAST 1250 and ELAST 7800. Long term in vivo degradation studies indicated that both elastomers undergo bulk hydrolysis along with surface erosion occurring due to the physiological environment. In the case of low cross-link density elastomers, the onset of mass loss was accompanied with an increase in both water uptake and sol content, whereas, in the case of high crosslink density elastomers, only the water uptake increased. This degradation pattern was due to crazing of the high crosslink density elastomers. ELAST 7800 cylinders were totally degraded, and ELAST 1250 cylinders had lost 80% of their mass, within 30 weeks. Aminor host reaction with minimal vascularity and inflammation was invoked, with a milder tissue response observed with more highly crosslinked cylinders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".